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Monte Carlo Methods in Finance
 
 
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Monte Carlo Methods in Finance [Hardcover]

Peter Jäckel , Peter Jaeckel
4.0 out of 5 stars  See all reviews (2 customer reviews)
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Product details

  • Hardcover: 238 pages
  • Publisher: John Wiley & Sons; Har/Com edition (26 Feb 2002)
  • Language English
  • ISBN-10: 047149741X
  • ISBN-13: 978-0471497417
  • Product Dimensions: 17.5 x 2 x 25.2 cm
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (2 customer reviews)
  • Amazon Bestsellers Rank: 533,852 in Books (See Top 100 in Books)
  • See Complete Table of Contents

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Peter Jäckel
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Product Description

Product Description

An invaluable resource for quantitative analysts who need to run models that assist in option pricing and risk management. This concise, practical hands on guide to Monte Carlo simulation introduces standard and advanced methods to the increasing complexity of derivatives portfolios. Ranging from pricing more complex derivatives, such as American and Asian options, to measuring Value at Risk, or modelling complex market dynamics, simulation is the only method general enough to capture the complexity and Monte Carlo simulation is the best pricing and risk management method available.
The book is packed with numerous examples using real world data and is supplied with a CD to aid in the use of the examples.

From the Inside Flap

Monte Carlo Methods in Finance is an important reference for those working in investment banks, insurance and strategic management consultancy. Of particular importance are the many known variance reduction methods, and they are duly covered, not only in their own right, but also with respect to their potential combinations, and in the direct context of realistic applications. Most notably, the issue of the reliability of low–discrepancy numbers in high dimensions is discussed in detail. The book also contains an introduction to the theory of copulæ as an extension to the modelling of correlation of financial securities. An entire chapter is dedicated to the evaluation of interest rate derivatives in the Brace–Gatarek–Musiela/Jamshidian framework by the aid of fast–convergence Monte Carlo simulations. What′s more, for the first time, this book also gives a description of the construction of non–recombining trees. Whilst non–recombining trees are usually not viable in a production environment, they often are the very tool of last resort when Monte Carlo approximations to problems such as Bermudan swaptions are to be tested, and the tricks for the construction of non–recombining trees presented in this book are invaluable for that purpose.

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Customer Reviews

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Most Helpful Customer Reviews
2 of 3 people found the following review helpful
Outstanding text 5 April 2007
Format:Hardcover
Jaeckel's book is an outstanding one and I will be using it for computational finance teaching at King's College London. Its many strengths include a proper appreciation of the importance of quantile functions (inverse CDFs) and discussions of different approaches to multivariate simulation including copula techniques (introductory) and low-discrepancy sequence methods (more detailed). Jaeckel carefully explains why a long-standing standard approaches to Normal simulation (Box-Muller) is problematic, and includes a helpful chapter on managing "bad" correlation matrices, which is vital for multivariate simulation. Variance reduction is discussed in detail. Applications focus more on the interest rate side and BGM models, and there is little on modern Monte Carlo methods for American options. So while this book does not cover everything, what it does do is done brilliantly.
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13 of 25 people found the following review helpful
By A Customer
Format:Hardcover
The book is ok, but the title is only partly what the book is about. I have counted 90 pages truly about Monte Carlo. What have copulae go to do with MC? Why would I want to 'salvage a correlation matrix' if I am looking for MC ideas?
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Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:  8 reviews
63 of 70 people found the following review helpful
Solid gold 14 May 2002
By A Customer - Published on Amazon.com
Format:Hardcover
Conflict of interest pervades the field of finance on every level including the intellectual level.

Often you might find books reviewed most favorably by
leading academic researchers to fall far short of the praise constituting a legal liability for the author's employer and
inducing a suspicion that the reviewer had material interests at stake.

For this reason we are grateful that Amazon has a liberal return policy. This book however you will not want to send back.

It hits the mark in several important aspects:

1. Level of detail.
The presentation is detailed enough for you to be able to translate the description into computer code but not so detailed that this step is immediate.
This allows an elegant and fluent style of writing.
Descriptions that are detailed enough to translate into code immediately almost certainly lack aesthetic qualities and one usually does not read them again them once the relevant information has been extracted. This is not the case here. I find myself browsing the material again after some algorithm has already been implemented and enjoying the experience.
The author has the ability to articulate complicated concepts clearly and without resort to heavy notation.

2. Mathematical rigour.

The mathematics is impeccable. In my own experience this can be said of fewer than 10% of the books in the field of finance.
The prerequisites are minimal. You have to know the most basic properties of Brownian motion (barely more than the definition)
and be familiar with the notion of a probability density.
Nonetheless several highly interesting subjects are treated in much detail (for example effective dimensionality reduction in conjunction with the application of low discrepancy sequences).

3. Choice of subject.

The techniques discussed are those used by leading investment banks. This is unsurprising since the author himself works at such an institution. The book is quite different from one devoted to Monte Carlo methods in physics, genetics or polymer science.

4. Physical appearance.

Page size, page layout, font selection and binding are all of high quality. The book has a wealth of diagrams communicating interesting information.

I love it and believe that you will too.

63 of 82 people found the following review helpful
I can NOT follow the math and NO CODE! 24 Aug 2002
By A Customer - Published on Amazon.com
Format:Hardcover|Amazon Verified Purchase
You better already know the basics of Monte Carlo Simulation
to get anything out of the book.

I STRONGLY disagree with one reviewer who thinks
all one needs to know is :
1) The definition of Brownian Motion and
2) What a Probability distribution is.
FAT chance.

The book requires knowing Linear Algebra, Probability,
PDEs, Stochastic Modelling, and SDEs to be of any use.

Where's the CODE, baby!
There are very few examples put into code!

One reviewer on Amazon.com, says the book is so
detailed you don't need code. Funny, I have never
seen anything "so detailed" that an example (code)
would make the explanation less clear!

22 of 29 people found the following review helpful
for Quants only 24 Jun 2003
By Franco Arda - Published on Amazon.com
Format:Hardcover
if you're a quant, you might really love this book

if you're a person who wants to have a "basic" understanding how to use MC for consulting or product pricing with examples, you got the wrong book (not mentioning that your maths must be pretty good).

if you're looking for an Excel example on how to price some basic options, i highly recommend Jackson & Staunton or Wilmott.

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